You're reading from Python Data Science Essentials. - Third Edition

Product typeBook

Published inSep 2018

Reading LevelIntermediate

PublisherPackt

ISBN-139781789537864

Edition3rd Edition

Languages

Python

Tools

Scikit-learn

Concepts

Data Science

Author (1)

Alberto Boschetti

Introducing EDA

Exploratory data analysis (EDA), or data exploration, is the first step in the data science process. John Tukey coined this term in 1977 when he first wrote his, book Exploratory Data Analysis, emphasizing the importance of EDA. EDA is required to understand the dataset better, check its features and its shape, validate some first hypothesis that you have in mind, and get a preliminary idea about the next step that you want to pursue in subsequent subsequent data science tasks.

In this section, you will work on the Iris dataset, which was already used in the previous chapter. First, let's load the dataset:

In: import pandas as pd
    iris_filename = 'datasets-uci-iris.csv'
    iris = pd.read_csv(iris_filename, header=None, 
            names= ['sepal_length', 'sepal_width', 
            'petal_length', 'petal_width...

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Python Data Science Essentials. - Third Edition

Published in: Sep 2018Publisher: PacktISBN-13: 9781789537864

Author (1)

Alberto Boschetti

Alberto Boschetti is a data scientist with expertise in signal processing and statistics. He holds a Ph.D. in telecommunication engineering and currently lives and works in London. In his work projects, he faces challenges ranging from natural language processing (NLP) and behavioral analysis to machine learning and distributed processing. He is very passionate about his job and always tries to stay updated about the latest developments in data science technologies, attending meet-ups, conferences, and other events.
Read more about Alberto Boschetti

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